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Criterion
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of Lean Startup with its method-specific working model.
Innovation
Lean Startup
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Purposedifferent
ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.
Complexitydifferent
MediumMediumMediumLow
Timedifferent
2–4 h review as a planning range; preparation and evaluation additional1-5 TageWochen bis Monate je Lernzyklus25-40 min
Participantsdifferent
Designers, developers as users, and facilitationNutzertraffic2-81-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsClick Data, Interest Signal, Learning DecisionHypothesis list, MVPs, Learning reports, Pivot or persevere decisionLearning Card with evidence and next action
Tags1 shared
ArchitectureEngineeringFeedbackValidationTasks
ValidationExperimentsDemandDiscovery
LeanStartupValidationMVP
ExperimentsValidationDiscoveryLearning
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